ó
    <Ð¦iŽ	  ã                   óR  • S r SSKrSSKJs  Jr  SSKJr  SSKJ	r	  SSK
JrJr  / SQrS r\R                  " \R                   SS	9r\" S
5      \	R$                  " SSSSS5      S\R&                  S\R(                  S\R(                  S\S\S\4S j5       5       r\" S5      \	R$                  " SSS5      S\R&                  S\R(                  S\R(                  S\4S j5       5       r\" S5      \	R$                  " SS5      SS\R&                  S\R(                  S\4S jj5       5       rg)aÉ  This file exports ONNX ops for opset 20.

Note [ONNX Operators that are added/updated in opset 20]

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
https://github.com/onnx/onnx/blob/main/docs/Changelog.md#version-20-of-the-default-onnx-operator-set
New operators:
    AffineGrid
    ConstantOfShape
    DFT
    Gelu
    GridSample
    ImageDecoder
    IsInf
    IsNaN
    ReduceMax
    ReduceMin
    RegexFullMatch
    StringConcat
    StringSplit
é    N)Ú_C)Úsymbolic_helper)Ú	jit_utilsÚregistration)Ú_grid_samplerÚ_affine_grid_generatorÚgeluc                 ó&   • U S:X  a  S$ U S:X  a  S$ U $ )NÚbilinearÚlinearÚbicubicÚcubic© )Úmode_ss    ÚZ/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/torch/onnx/symbolic_opset20.pyÚconvert_grid_sample_moder   &   s(   € à˜jÓ(ˆðØ9?À9Ó9L¨gðØRXðó    é   )Úopsetzaten::grid_samplerÚvÚiÚbÚgÚinputÚgridÚ	mode_enumÚpadding_mode_enumÚalign_cornersc           	      óB  • [         R                  R                  5        VVs0 s H  u  pgXv_M	     snnU   n[        U5      n[         R                  R                  5        VVs0 s H  u  pgXv_M	     snnU   n	U R                  SUU[        U5      UU	S9$ s  snnf s  snnf )NÚ
GridSample)Úalign_corners_ir   Úpadding_mode_s)ÚFÚGRID_SAMPLE_INTERPOLATION_MODESÚitemsr   ÚGRID_SAMPLE_PADDING_MODESÚopÚint)
r   r   r   r   r   r   Úkr   r   r"   s
             r   r   r   /   s¨   € ô  !×@Ñ@×FÑFÔHÔIÒH‘tqˆaŠdÑHÒIÈ)ÑT€Fä% fÓ-€FÜ'(×'BÑ'B×'HÑ'HÔ'JÔKÒ'J™t˜qa’dÑ'JÒKØñ€Nð 4‰4ØØØÜ˜MÓ*ØØ%ð ð ð ùó Jùó Ls   ¢BÁ#Bzaten::affine_grid_generatorÚthetaÚsizec                 ó8   • U R                  SUU[        U5      S9$ )NÚ
AffineGrid)r!   )r'   r(   )r   r*   r+   r   s       r   r   r   I   s+   € ð 4‰4ØØØÜ˜MÓ*ð	 ð ð r   z
aten::geluÚsÚselfÚapproximatec                 ó"   • U R                  SXS9$ )NÚGelu)Úapproximate_s)r'   )r   r/   r0   s      r   r	   r	   Y   s   € ð 4‰4˜ˆ4Ð8Ð8r   )Únone)Ú__doc__Ú	functoolsÚtorch.nn.functionalÚnnÚ
functionalr#   Útorchr   Ú
torch.onnxr   Útorch.onnx._internalr   r   Ú__all__r   ÚpartialÚonnx_symbolicÚ_onnx_symbolicÚ
parse_argsÚGraphContextÚValuer(   Úboolr   r   Ústrr	   r   r   r   Ú<module>rF      so  ðñó, ç Ð Ý Ý &ß 8ò >€òð ×"Ò" <×#=Ñ#=ÀRÑH€ñ Ð$Ó%Ø×Ò˜C  c¨3°Ó4ðØ×Ñðà8‰8ðð (‰(ðð ð	ð
 ðð óó 5ó &ðñ0 Ð-Ó.Ø×Ò˜C  cÓ*ðØ×Ñðà8‰8ðð (‰(ðð ó	ó +ó /ðñ ÓØ×Ò˜C Ó%ñ9ˆI×"Ñ"ð 9¨"¯(©(ð 9Àô 9ó &ó ñ9r   